The permeability is the most important parameter that indicates how efficient the reservoir fluids flow through the rock pores to the wellbore. Well-log evaluation and core measurements techniques are typically used to estimate it. In this paper, the permeability has been predicted by using classical and Flow zone indicator methods. A comparison between the two methods shows the superiority of the FZI method correlations, these correlations can be used to estimate permeability in un-cored wells with a good approximation.

This paper investigates the effect of magnetohydrodynamic (MHD) of an incompressible generalized burgers’ fluid including a gradient constant pressure and an exponentially accelerate plate where no slip hypothesis between the burgers’ fluid and an exponential plate is no longer valid. The constitutive relationship can establish of the fluid model process by fractional calculus, by using Laplace and Finite Fourier sine transforms. We obtain a solution for shear stress and velocity distribution. Furthermore, 3D figures are drawn to exhibit the effect of magneto hydrodynamic and different parameters for the velocity distribution.

wind load coefficient

The performance of sewage pumps stations affected by many factors through its work time which produce undesired transportation efficiency. This paper is focus on the use of artificial neural network and multiple linear regression (MLR) models for prediction the major sewage pump station in Baghdad city. The data used in this work were obtained from Al-Habibia sewage pump station during specified records- three years in Al-Karkh district, Baghdad. Pumping capability of the stations was recognized by considering the influent input importance of discharge, total suspended solids (TSS) and biological oxygen demand (BOD).  In addition, the chemical oxygen demands (COD), pH and chloride (Cl). The proposed model performanc

This growing interest of the international scientific specialized commissions is due to the role that the audit committee can play, as one of companies’ governance tools, to increase the accuracy and transparency of the financial information disclosed by the companies, through its oversight role on the process of preparing financial reports, its supervision on the internal audit function within the companies, and supporting its independency, as well as coordinating the efforts between the internal control unites and the external auditor represented by the (Board of Supreme Audit) to clear the observations and irregularities in order to reduce the fraud cases.

This research was built on an applied sample of audit committee works

Nanofluids are proven to be efficient agents for wettability alteration in subsurface applications including enhanced oil recovery (EOR). Nanofluids can also be used for CO2-storage applications where the CO2-wet rocks can be rendered strongly water-wet, however no attention has been given to this aspect in the past. Thus in this work we presents contact angle (θ) measurements for CO2/brine/calcite system as function of pressure (0.1 MPa, 5 MPa, 10 MPa, 15 MPa, and 20 MPa), temperature (23 °C, 50 °C and 70 °C), and salinity (0, 5, 10, 15, and 20% NaCl) before and after nano-treatment to address the wettability alteration efficiency. Moreover, the effect of treatment pressure and temperature, treatment fluid concentration (SiO2 wt%) and

Metasurface polarizers are essential optical components in modern integrated optics and play a vital role in many optical applications including Quantum Key Distribution systems in quantum cryptography. However, inverse design of metasurface polarizers with high efficiency depends on the proper prediction of structural dimensions based on required optical response. Deep learning neural networks can efficiently help in the inverse design process, minimizing both time and simulation resources requirements, while better results can be achieved compared to traditional optimization methods. Hereby, utilizing the COMSOL Multiphysics Surrogate model and deep neural networks to design a metasurface grating structure with high extinction rat

Single-photon detection concept is the most crucial factor that determines the performance of quantum key distribution (QKD) systems. In this paper, a simulator with time domain visualizers and configurable parameters using continuous time simulation approach is presented for modeling and investigating the performance of single-photon detectors operating in Gieger mode at the wavelength of 830 nm. The widely used C30921S silicon avalanche photodiode was modeled in terms of avalanche pulse, the effect of experiment conditions such as excess voltage, temperature and average photon number on the photon detection efficiency, dark count rate and afterpulse probability. This work shows a general repeatable modeling process for significant perform